CN113742958B - Calculation method of rock digital characterization model based on physical element theory - Google Patents
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Abstract
The invention discloses a calculation method of a rock digital characterization model based on a physical element theory, which comprises the following steps: s1: deriving a rock digital characterization model; s2: storing the design meta information; the invention tries to introduce the idea of the infinitesimal method into the digital representation of the rock, takes account of the microscopic characteristics such as fracture information, mineral physical information, mineral mechanical information and the like, discretizes the problem of the digital representation of the rock, regards the rock as a cube consisting of countless infinitesimal units, and researches the characteristics of the infinitesimal units or the infinitesimal units so as to achieve the aim of judging the characteristics of the integral structure of the rock.
Description
Technical Field
The invention relates to the field of geology, in particular to a calculation method of a rock digital characterization model based on a physical element theory.
Background
Based on the philosophy that the things themselves determine their characteristics and the magnitude reflects the variation of the characteristics, the inherent properties of things are analyzed by studying various variations of the characteristics and magnitude of the things. The theory of matter is a method proposed in Cai Wenyu 1988 for solving the problem of compatibility and incompatibility, which takes the names, characteristics and magnitudes of matters as basic elements for describing matters, and takes ordered triplets as basic elements for describing matters, namely R= (N, c, v) where R represents the matter element, N represents the name of the matters under study, c is the characteristics of the matters, and v is the magnitudes of the characteristics of the matters.
The idea of the infinitesimal method is to integrate the studied things into zero, start from the tiny part of the things, analyze infinitesimal first and then solve the infinitesimal group, thereby achieving the optimal solution from local to whole. The rock cannot directly observe internal microscopic structural information such as fracture information, mineral physical information, mineral mechanical information and the like, and a certain technical means is needed. For example, the slit information is subjected to statistical analysis according to a scanning image by using a CT tomography experiment to obtain microscopic structural characteristics; mineral physical information, and obtaining mineral category, content and the like by utilizing a mineral identification experiment; and (3) mineral mechanics information, namely according to the mineral physical information and the joint rock production area, inquiring a mineral sheet microscopic image database in the public information to obtain the mineral mechanics information.
Based on the method, the idea of the infinitesimal method is tried to be introduced into the digital representation of the rock, the microscopic characteristics such as fracture information, mineral physical information, mineral mechanical information and the like are considered, the problem of the digital representation of the rock is discretized, the rock is regarded as a cube composed of countless infinitesimal units, and the characteristics of the infinitesimal units or the infinitesimal units are studied, so that the aim of judging the characteristics of the integral structure of the rock is fulfilled.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a calculation method of a rock digital characterization model based on a matter element theory.
The technical scheme adopted by the invention is as follows: a calculation method of a rock digital characterization model based on a physical element theory comprises the following steps:
s1: deriving a stone digital characterization model;
s2: the design meta-information is stored.
Preferably, S1 comprises the substeps of
S11: assuming that the rock sample specification is a cube of L×W×H, discretizing the cube into n x ny×nz small cube grids by adopting the idea of a infinitesimal method, wherein each cube small grid corresponds to a local area of an actual rock and is called rock infinitesimal;
s12: after the discrete micro-elements are divided, nx micro-elements exist in the x direction, ny micro-elements exist in the y direction, and nz micro-elements exist in the z direction, so that the total of the nx, the ny and the nz micro-elements exist;
s13: characterizing the infinitesimal by using the matter element idea, wherein the attribute of each infinitesimal can be defined and represented;
s14: the entire cubic rock sample may be represented in the form of a vector set, r= (R 1 ,R 2 ,...,R m ,...,R n ) T ,n＝nx×ny×nz，
Wherein R is m ＝(N m ,c m ,v m ) Representing the mth representative element formed by the mth representative element in the cube after the introduction of the element idea, N m Representing the name of the m-th bin studied in the cube, c m Representing a feature of the object, v m Representing corresponding feature values of the object;
s15: since the characteristics of things are not unique, more features can be introduced to enable detailed presentation, i.e
s16: according to the requirement of the storage rule, two batches of different points are required to be combined and stored for the convenience of future retrieval, so that the numbers of all the primitives are given after the discussion of all the primitive points is completed;
s17: for digital characterization, discretized cube microelements are regarded as stacked by thin plates with a certain thickness, wherein the thickness of the thin plates is H/w, and each thin plate can be divided into m multiplied by n small cube microelements according to columns and rows;
s18: according to the stacking precision, finally forming a sheet cube microcell cross-section effect diagram;
s19: the spirit of the object element theory is utilized to represent the infinitesimal, and the attribute of each infinitesimal can be defined and represented.
Preferably, S19 comprises the sub-steps of:
s191: the stacked sheets are numbered 1,2,3, … … w in order from bottom to top, and the entire cubic sample can be represented as vector r= (R 1 ,R 2 ,R 3 ……R w ) T Wherein R is 1 ,R 2 ,R 3 … … the elements in each sheet are stacked and the elements of each face are numbered in rows and columns to form a two-dimensional vector R (i,j) Wherein 1.ltoreq.i.ltoreq.m, 1.ltoreq.j.ltoreq.n, and the microcell network of each face may be represented by the following formula:
s192: considering rock as being composed of micro-elements, each representing a local micro-area of the rock, the interior of the rock having various micro-features, so also represented by rock micro-elements;
s193: inputting by adopting a relation model according to the thought of a database;
s194: the microscopic features of the main study are pores, fissures and minerals, which are divided into three large modules, each of which can in turn be divided into several sub-modules;
s195: there is also a correlation between the microelements, there is a correlation between the microelements covered by the area where the crack exists and the surrounding adjacent microelements, there is a difference between the characteristics of the surrounding microelements and the characteristics of the microelements, the difference causes distinct effects, a range is required for correlation, the range is a spatial range, a public derivation is required, and for simple processing, the relevant microelements are in three directions of x/y/z, and the diagonal angle is not considered;
wherein: x? Y? And z? The values of r, c and l are required to be determined together according to the actual size of the rock sample and the size of the infinitesimal coordinate related to the rock sample;
s196: the data in the infinitesimal is a plurality of two-dimensional tables, and all the information is contained in the tables, wherein three types of tables form a system;
s197: and (3) representing the rock mesoscopic structure information by utilizing the micro-metadata set, and constructing a physical element model of the rock by combining the micro-metadata set, so as to finally form a rock digital representation model.
Preferably, S2 comprises the sub-steps of:
s21: the rock is digitally represented by adopting a physical element theory, three types of infinitesimal information are required to be determined, and the three types of microscopic structure information are required to be obtained by means of three testing means and have the characteristics of variability such as discrete, irregular and the like;
s22: according to the spatial position relation of each piece of material element information, different physical properties of the material element information are combined, meanwhile, in consideration of convenience of future data storage and retrieval, various cracks, physical properties and the like are required to be subjected to large-class division storage, different classes are obtained, and according to the different classes, the material element information of the rock is respectively stored, and different types of data tables are established;
s23: mutual characterization relation for physical rock and digital rock: a first type of physical rock, determining a target rock by traversing the rock number, and determining information such as sampling places, physical states and the like; the second type of digital rock is used for inquiring the object id to obtain an object model of the digital rock, and inquiring the infinitesimal number to locate infinitesimal information groups so as to further determine information such as cracks, mineral physics, mineral mechanics and the like.
The rock digital characterization model calculation method based on the physical element theory has the following beneficial effects:
1. the microscopic characteristic information such as crack information, mineral physical information, mineral mechanical information and the like in the rock is characterized and stored in a micro-element mode, and a plurality of microscopic information of the rock is integrated by utilizing a physical element theory, so that a digital characterization scheme for really realizing the microscopic information of the rock is formed.
2. The mesoscopic information such as crack information, mineral physical information, mineral mechanics and the like in the rock is characterized by microelements.
3. By contrast in the loading process r= (c, m, s) x,y,z And analyzing the correlation property of the fracture and the rock physical property in the rock damage development process by the change of each infinitesimal information in the primitive model, and realizing the digital characterization of the rock and the damage process.
Drawings
FIG. 1 is a diagram of a rock discretization (a) a rock sample (b) a discrete microelements
FIG. 2 is a schematic view of the effect of the discrete back-element model (a) rock material element model (b) discrete element
Fig. 3 is a sheet stacking effect demonstration diagram (a) m×n small cube microelements (b) a sheet cube microelements cross-sectional effect diagram.
Fig. 4 is a cross-sectional effect diagram of a lamellar cube.
FIG. 5 is a schematic diagram of the infinitesimal correlation.
Fig. 6 is a graph of the relationship between physical rock and digital rock.
FIG. 7 is a flow chart for digital rock model construction.
FIG. 8 is a sample preparation.
FIG. 9 is a graph showing the three-dimensional visual effect of the fracture of the specimen HS-1 with 60% stress level (a) and 60% stress level (b) on the fracture space information table.
Fig. 10 is a three-dimensional visual effect diagram of mineral spatial distribution information (a) of the test piece HS-1 and mineral type and content information table (b) of the minerals.
Fig. 11 is a view showing three-dimensional visual effects of the mineral after interpolation of the distribution information (a) of rock physical properties (crystal scraps-quartz) after interpolation of rock mineral information and (b) of the information table after interpolation.
Fig. 12 shows the spatial distribution of the fractures after three-dimensional reconstruction of the rock fracture distribution information (a) and the rock fracture data information (b).
Fig. 13 shows the spatial distribution of rock properties (chip-quartz) initial distribution information (a) rock mineral content information (b) after three-dimensional reconstruction of the mineral information.
Fig. 14 shows the total data information after the petrophysical interpolation correction.
Fig. 15 is a diagram of a rock information storage structure.
Detailed Description
The following description of the embodiments of the present invention is provided to facilitate understanding of the present invention by those skilled in the art, but it should be understood that the present invention is not limited to the scope of the embodiments, and all the inventions which make use of the inventive concept are protected by the spirit and scope of the present invention as defined and defined in the appended claims to those skilled in the art.
1) Rock digital characterization model
Assuming that the rock sample has a cubic shape of lxwxh (fig. 1. A), the cubic shape is discretized into nx xny×nz small cubic grids (fig. 1. B) by adopting the idea of the infinitesimal method, and each small cubic grid corresponds to a local area of an actual rock, which is called a rock infinitesimal, and the rock infinitesimal at this time is just taken as a concept and cannot represent physical information of the rock.
As shown in fig. 2.A, the number of discrete microelements divided in the x direction is nx number of microelements, the y direction is ny number of microelements, and the z direction is nz number of microelements, so that the total number of microelements is nx×ny×nz.
The primitives are characterized by the concept of primitives, wherein the attribute of each primitive can be defined and represented.
The entire cubic rock sample may be represented in the form of a vector set, r= (R 1 ,R 2 ,...,R m ,...,R n ) T ,n＝nx×ny×nz，
Wherein R is m ＝(N m ,c m ,v m ) Representing the m-th representative infinitesimal in a cubeThe m number formed after entering the idea of the object represents the object, N m Representing the name of the m-th bin studied in the cube, c m Representing a feature of the object, v m Representing the corresponding feature quantity value of the object,
since the characteristics of things are not unique, more features can be introduced to enable detailed presentation, i.e
As shown in fig. 2.B, the m-th primitive case is shown.
Regarding specific numbering convention, separate discussions are required as it would involve a difference between the artificial segmentation points and the initial known experimental points.
According to the requirement of the storage rule, two batches of different points are required to be combined and stored for the convenience of future retrieval, so the numbers of all the primitives are given after the discussion of all the primitive points is completed.
For digital characterization, discretized cube microelements are regarded as being formed by stacking thin plates with a certain thickness, wherein the thickness of the thin plates is H/w, and each thin plate can be divided into m multiplied by n small cube microelements according to columns and rows (figure 3). Depending on the stacking accuracy, a cross-sectional effect map such as a slice cube microcell is finally formed (fig. 4).
The spirit of the object element theory is utilized to represent the infinitesimal, and the attribute of each infinitesimal can be defined and represented.
The stacked sheets are numbered 1,2,3, … … w in order from bottom to top, and the entire cubic sample can be represented as vector r= (R 1 ,R 2 ,R 3 ……R w ) T Wherein R is 1 ,R 2 ,R 3 … … the elements in each sheet are stacked and the elements of each face are numbered in rows and columns to form a two-dimensional vector R (i,j) (wherein 1.ltoreq.i.ltoreq.m, 1.ltoreq.j.ltoreq.n), the microcell network for each face may be represented by the following formula:
……，
the rock is considered to be made up of microelements, each of which represents a local mesoscopic region of the rock, the interior of which has various mesoscopic features, and so is also represented by rock microelements.
The key to the problem is the storage of the microscopic features, which are now entered using a relational model based on the ideas of the database.
The microscopic features of the main study are three categories of pores, fissures and minerals, divided into three large modules, each of which can in turn be divided into several sub-modules. For example, there are many parameters of the characteristics of the pores: volume, surface area, length, width, etc. so that a two-dimensional table can be formed, the pores also have corresponding coordinates, which can be correspondingly in the infinitesimal. Similarly, the fractures may be expressed in terms of a two-dimensional table with many microelements covered by each fracture. The same is true for mineral characteristics.
There is also a correlation between the microelements (fig. 5), there is a correlation between the microelements covered by the area where the crack exists and the surrounding adjacent microelements, there is a difference between the characteristics of the surrounding microelements and the characteristics of the microelements, this difference causes distinct effects, a range is required for correlation, this range is a spatial range, a public derivation is required, and for easy processing, the relevant microelements are selected in three directions of x/y/z, and no diagonal angle is considered.
Wherein: x? Y? And z? The values of r, c and l representing the current associated infinitesimal coordinates need to be determined jointly according to the actual size of the rock sample and the infinitesimal size.
The data in the infinitesimal is a plurality of two-dimensional tables, and all the information is contained in the tables, wherein three types of tables form a system. And (3) representing the rock mesoscopic structure information by utilizing the micro-metadata set, and constructing a physical element model of the rock by combining the micro-metadata set, so as to finally form a rock digital representation model.
2) Storage design of material element information
The rock is digitally represented by adopting the physical element theory, three types of micro-element information are required to be determined, and the three types of micro-structure information are required to be obtained by means of three test means and have the characteristics of variability such as discrete, irregular and the like.
According to the spatial position relation of each piece of material element information, different physical properties of the material element information are combined, meanwhile, in consideration of convenience of future data storage and retrieval, various cracks, physical properties and the like are required to be subjected to large-class division storage, different classes are obtained, and according to the different classes, the material element information of the rock is respectively stored, and different types of data tables are established.
Mutual characterization relation for physical rock and digital rock (fig. 6): a first type of physical rock, determining a target rock by traversing the rock number, and determining information such as sampling places, physical states and the like; the second type of digital rock is used for inquiring the object id to obtain an object model of the digital rock, and inquiring the infinitesimal number to locate infinitesimal information groups so as to further determine information such as cracks, mineral physics, mineral mechanics and the like.
As shown in fig. 7, a flow chart of a rock digital characterization model based on the primitive theory is shown.
In practice of this embodiment, first, a rock sample is selected
The experimental sample is selected to be red sandstone which contains gravels, and the mineral particle size is rich, so that CT scanning is easy to identify. To increase the accuracy and convincing of the experiment, the samples were cut into 5 standard cubes, as shown in FIG. 8, with dimensions of 100mm by 100mm, numbered HS-1, HS-2, HS-3, HS-4, HS-5. The cut sandstone is polished by a grinding stone, so that the non-parallelism of each section is ensured to be controlled within 0.02 mm.
Infinitesimal information acquisition
1) Rock fracture information
The rock fracture pattern under several stress gradients, such as 0%, 20%, 40%, 60%, 90% etc. stress gradients were obtained using a mechanical tester. After each loading to a certain stress gradient, CT tomography is carried out to obtain crack space information cx of each stress gradient rock i ×cy i ×cz i (i represents a stress gradient). FIG. 9a is a statistical table of fracture spatial information with a stress level of 60% that can be used to provide fracture spatial position, fracture morphology, and fracture volume equalization information for achieving three-dimensional visual characterization of fracture distribution using software (FIG. 9 b).
2) Rock mineral information
After the rock mechanical process is finished, carrying out discretization treatment on the rock, cutting the rock into rock blocks with x multiplied by y multiplied by z, and carrying out mineral component identification on the series of rock blocks to obtain phase information mx multiplied by my multiplied by mz of minerals such as mineral components, mineral content and the like. In fig. 10, after discretizing the rock, each rock slice is scanned by a polarized microscope to obtain phase information of mineral types, mineral contents and the like in the rock slice (fig. 10 a), and three-dimensional visual characterization of mineral spatial distribution is realized by software (fig. 10 b).
3) Information on mineral mechanics
The mineral mechanics information base is consulted to obtain the mechanical information sx x sy x sz of each mineral component, in a specific case similar to "2) rock mineral information". And will not be described in detail herein.
Micro-metadata set construction
1) Precision unified processing of three types of mesoscopic parameters
The characteristic of discrete and uniform distribution is realized by utilizing the representative infinitesimal information artificially generated by rules, and the mineral composition distribution condition at any point (artificially generated rule point) in the rock can be obtained by utilizing the known physical property information based on the Kriging interpolation principle by taking rock mineral information as an example. As shown in fig. 11, a) is a mineral data information table after interpolation processing, and b) is a three-dimensional visual map drawn using the information table.
Based on the idea of the matter element-infinitesimal method, the fracture information c, the mineral physical information and the mineral mechanical information are filled into infinitesimal, and the infinitesimal information is integrated by utilizing a matter element model to form R= (c, m, s) x,y,z Is described herein). Based on the philosophy that "things themselves determine their characteristics, and the magnitude reflects the change of characteristics", r= (c, m, s) is utilized x,y,z The change of each infinitesimal information in the object model is used for analyzing the intrinsic attribute of the object model, so that the digitalized characterization of the rock is achieved.
Infinitesimal information set
(1) First kind of fracture information
The principle of the CT tomography method is that the CT image of the rock is used for gray scale treatment, and according to different gray scale values, the crack data in the rock can be obtained on the premise of meeting a certain threshold standard, and the specific information is shown in figure 12.
(2) Second, mineral physical information
Taking physical property information as an example, the overall structure of the rock interior and the mineral composition distribution can be obtained by using a polarization microscope, and specific information thereof is shown in fig. 13.
(3) Third category, mineral mechanics information
The mechanical information of different minerals has differences, and the mechanical information of the minerals can be obtained by inquiring a mineral flake microscopic image database in the public information in combination with the rock production place. The spatial coordinates of the mineral mechanics information are consistent with the position information and the storage information of the mineral physical information, and are not discussed herein.
Precision matching of different infinitesimal information
Because three types of microscopic information are obtained by three test means, the problems of precision difference and the like exist. After the initial interpolation is completed, the physical interpolation information needs to be corrected, and the accuracy of experimental data of the physical information is relatively low due to reasons of experimental precision, equipment condition limitation and the like, so that the information at the artificial point obtained by interpolation may contain more error information. The main principle of the method is as follows: based on the characteristics of the CT experiment, the experimental precision is high, the obtained experimental data is more reliable, and the correction of the data of the physical property interpolation by using the fracture data generated by the CT experiment is feasible in theory and practice, that is, the position where the fracture exists (each point contains a small radius) should not have a certain physical property.
Therefore, the physical interpolation data is corrected by utilizing the fracture data and the radius information, namely, the physical interpolation result in the fracture point radius range needs to be removed. The results of the physical property interpolation correction are shown in fig. 14.
In the table above, the first column indicates the type of data point (0 indicates an artificially generated data point, 1 indicates an initial fracture data point, 2 indicates an initial physical data point), the 2 nd to 4 th columns indicate coordinate information of points, and the x, y, and z axes are respectively indicated in order, and the 5 th column indicates fracture information, and NaN indicates that fracture information at the point does not exist. Columns 6 to 12 each show various physical property information, and NaN similarly shows that the physical property information at this point does not exist.
Rock digital characterization model construction
All information of the rock material elements, including position information, fracture information, physical property information, mechanical information and the like of various material element points, and finally the construction of the rock digital characterization model is completed (figure 15).
Claims (2)
1. The calculation method of the rock digital characterization model based on the physical element theory is characterized by comprising the following steps of:
s1: deriving a rock digital characterization model;
s2: storing the design meta information;
the step S1 comprises the following substeps:
s11: assuming that the rock sample specification is a cube of L×W×H, discretizing the cube into n x ny×nz small cube grids by adopting the idea of a infinitesimal method, wherein each cube small grid corresponds to a local area of an actual rock and is called rock infinitesimal;
s12: after the discrete micro-elements are divided, nx micro-elements exist in the x direction, ny micro-elements exist in the y direction, and nz micro-elements exist in the z direction, so that the total of the nx, the ny and the nz micro-elements exist;
s13: characterizing the primes by using the spirit of the primes, wherein the attribute of each prime is defined and represented;
s14: the whole cubic rock sample is represented in the form of a vector set, r= (R 1 ,R 2 ,...,R m ,...,R n ) T ,n＝nx×ny×nz，
Wherein R is m ＝(N m ,c m ,v m ) Representing the mth representative element formed by the mth representative element in the cube after the introduction of the element idea, N m Representing the name of the m-th bin studied in the cube, c m Representing a feature of the object, v m Representing corresponding feature values of the object;
s15: since the characteristics of things are not unique, in order to be able to make detailed representations, more characteristics are introduced, i.e
s16: according to the requirement of the storage rule, two batches of different points are required to be combined and stored for the convenience of future retrieval, so that the numbers of all the primitives are given after the discussion of all the primitive points is completed;
s17: for digital characterization, discretized cube microelements are regarded as stacked by thin plates with a certain thickness, wherein the thickness of the thin plates is H/w, and each thin plate can be divided into m multiplied by n small cube microelements according to columns and rows;
s18: according to the stacking precision, finally forming a sheet cube microcell cross-section effect diagram;
s19: characterizing the infinitesimal by utilizing the thought of the object element theory, wherein the attribute of each infinitesimal is defined and represented;
the step S19 includes the sub-steps of:
s191: the stacked sheets are numbered 1,2,3 and … … w in order from bottom to top, and the whole cubic sample is expressed as a vector r= (R 1 ,R 2 ,R 3 ……R w ) T Wherein R is 1 ,R 2 ,R 3 … … the elements in each sheet are stacked and the elements of each face are numbered in rows and columns to form a two-dimensional vector R (i,j) Wherein i is equal to or less than 1 and equal to or less than m, j is equal to or less than 1 and equal to or less than n, and the microcell mesh of each face is represented by the following formula:
s192: considering rock as being composed of micro-elements, each representing a local micro-area of the rock, the interior of the rock having various micro-features, so also represented by rock micro-elements;
s193: inputting by adopting a relation model according to the thought of a database;
s194: the microscopic features studied are three categories, pore, fissure and mineral, divided into three large modules, each of which can in turn be divided into several sub-modules;
s195: there is also a correlation between the microelements, there is a correlation between the microelements covered by the area where the crack exists and the surrounding adjacent microelements, there is a difference between the characteristics of the surrounding microelements and the characteristics of the microelements, the difference causes distinct effects, a range is required for correlation, the range is a spatial range, a public derivation is required, and for simple processing, the relevant microelements are in three directions of x/y/z, and the diagonal angle is not considered;
wherein: x is x ？ 、y ？ And z ？ The values of r, c and l are required to be determined together according to the actual size of the rock sample and the size of the infinitesimal coordinate related to the rock sample;
s196: the data in the infinitesimal is a plurality of two-dimensional tables, and all the information is contained in the tables, wherein three types of tables form a system;
s197: and (3) representing the rock mesoscopic structure information by utilizing the micro-metadata set, and constructing a physical element model of the rock by combining the micro-metadata set, so as to finally form a rock digital representation model.
2. The method for computing a numerical representation model of rock based on the primitive theory according to claim 1, wherein S2 comprises the following sub-steps:
s21: the rock is digitally represented by adopting a physical element theory, three types of infinitesimal information are required to be defined, and the three types of microscopic structure information are required to be obtained by means of three test means and have discrete irregular difference characteristics;
s22: according to the spatial position relation of each piece of material element information, different physical properties of the material element information are combined, meanwhile, in consideration of convenience of future data storage and retrieval, large-class division storage is needed for various fracture physical properties, different classes are obtained, and according to the different classes, the material element information of the rock is stored respectively, and different types of data tables are built;
s23: mutual characterization relation for physical rock and digital rock: the method comprises the steps of determining a first type of physical rock, determining a target rock by traversing rock numbers, and determining physical state information of a sampling place; and inquiring the object id of the second type of digital rock to obtain an object model of the digital rock, inquiring the infinitesimal number to locate infinitesimal information groups, and further determining fracture, mineral physics and mineral mechanics information.
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